Reconceptualizing Knowledge Management: Heterogeneous Impacts of Generative and Recommendative AI

Abstract

This study explores the transformative roles of Generative AI (GenAI) and Recommendative AI (RecAI) in knowledge management (KM), emphasizing their distinct contributions to organizational innovation. GenAI, exemplified by platforms like GPT-4 and DALL•E, drives exploratory innovation by enabling novel knowledge creation through combinatorial creativity, rapid prototyping, and hypothesis generation in R&D and product design. Conversely, RecAI enhances exploitative innovation by leveraging machine learning to curate and personalize knowledge, reducing cognitive overload and facilitating just-in-time learning. KM is framed as a dynamic capability critical for sustaining competitive advantage, with AI augmenting processes like knowledge creation, storage, dissemination, application, and refinement. However, challenges such as GenAI’s potential for hallucinated content and RecAI’s risk of filter bubbles necessitate adaptive governance to ensure authenticity, transparency, and epistemic diversity. The study proposes an integrated framework combining digital capabilities, strategic alignment, and agile governance to optimize AI-enabled KM in innovation-driven organizations, aligning technological adoption with ethical and strategic priorities.

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